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"""
Pure python blurhash decoder with no additional dependencies, for
both de- and encoding.
Very close port of the original Swift implementation by Dag Ă…gren.
"""
import math
# Alphabet for base 83
alphabet = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz#$%*+,-.:;=?@[]^_{|}~"
alphabet_values = dict(zip(alphabet, range(len(alphabet))))
def base83_decode(base83_str):
"""
Decodes a base83 string, as used in blurhash, to an integer.
"""
value = 0
for base83_char in base83_str:
value = value * 83 + alphabet_values[base83_char]
return value
def base83_encode(value, length):
"""
Decodes an integer to a base83 string, as used in blurhash.
Length is how long the resulting string should be. Will complain
if the specified length is too short.
"""
if int(value) // (83 ** (length)) != 0:
raise ValueError("Specified length is too short to encode given value.")
result = ""
for i in range(1, length + 1):
digit = int(value) // (83 ** (length - i)) % 83
result += alphabet[int(digit)]
return result
def srgb_to_linear(value):
"""
srgb 0-255 integer to linear 0.0-1.0 floating point conversion.
"""
value = float(value) / 255.0
if value <= 0.04045:
return value / 12.92
return math.pow((value + 0.055) / 1.055, 2.4)
def sign_pow(value, exp):
"""
Sign-preserving exponentiation.
"""
return math.copysign(math.pow(abs(value), exp), value)
def linear_to_srgb(value):
"""
linear 0.0-1.0 floating point to srgb 0-255 integer conversion.
"""
value = max(0.0, min(1.0, value))
if value <= 0.0031308:
return int(value * 12.92 * 255 + 0.5)
return int((1.055 * math.pow(value, 1 / 2.4) - 0.055) * 255 + 0.5)
def blurhash_components(blurhash):
"""
Decodes and returns the number of x and y components in the given blurhash.
"""
if len(blurhash) < 6:
raise ValueError("BlurHash must be at least 6 characters long.")
# Decode metadata
size_info = base83_decode(blurhash[0])
size_y = int(size_info / 9) + 1
size_x = (size_info % 9) + 1
return size_x, size_y
def blurhash_decode(blurhash, width, height, punch = 1.0, linear = False):
"""
Decodes the given blurhash to an image of the specified size.
Returns the resulting image a list of lists of 3-value sRGB 8 bit integer
lists. Set linear to True if you would prefer to get linear floating point
RGB back.
The punch parameter can be used to de- or increase the contrast of the
resulting image.
As per the original implementation it is suggested to only decode
to a relatively small size and then scale the result up, as it
basically looks the same anyways.
"""
if len(blurhash) < 6:
raise ValueError("BlurHash must be at least 6 characters long.")
# Decode metadata
size_info = base83_decode(blurhash[0])
size_y = int(size_info / 9) + 1
size_x = (size_info % 9) + 1
quant_max_value = base83_decode(blurhash[1])
real_max_value = (float(quant_max_value + 1) / 166.0) * punch
# Make sure we at least have the right number of characters
if len(blurhash) != 4 + 2 * size_x * size_y:
raise ValueError("Invalid BlurHash length.")
# Decode DC component
dc_value = base83_decode(blurhash[2:6])
colours = [(
srgb_to_linear(dc_value >> 16),
srgb_to_linear((dc_value >> 8) & 255),
srgb_to_linear(dc_value & 255)
)]
# Decode AC components
for component in range(1, size_x * size_y):
ac_value = base83_decode(blurhash[4+component*2:4+(component+1)*2])
colours.append((
sign_pow((float(int(ac_value / (19 * 19))) - 9.0) / 9.0, 2.0) * real_max_value,
sign_pow((float(int(ac_value / 19) % 19) - 9.0) / 9.0, 2.0) * real_max_value,
sign_pow((float(ac_value % 19) - 9.0) / 9.0, 2.0) * real_max_value
))
# Return image RGB values, as a list of lists of lists,
# consumable by something like numpy or PIL.
pixels = []
for y in range(height):
pixel_row = []
for x in range(width):
pixel = [0.0, 0.0, 0.0]
for j in range(size_y):
for i in range(size_x):
basis = math.cos(math.pi * float(x) * float(i) / float(width)) * \
math.cos(math.pi * float(y) * float(j) / float(height))
colour = colours[i + j * size_x]
pixel[0] += colour[0] * basis
pixel[1] += colour[1] * basis
pixel[2] += colour[2] * basis
if linear == False:
pixel_row.append([
linear_to_srgb(pixel[0]),
linear_to_srgb(pixel[1]),
linear_to_srgb(pixel[2]),
])
else:
pixel_row.append(pixel)
pixels.append(pixel_row)
return pixels
def blurhash_encode(image, components_x = 4, components_y = 4, linear = False):
"""
Calculates the blurhash for an image using the given x and y component counts.
Image should be a 3-dimensional array, with the first dimension being y, the second
being x, and the third being the three rgb components that are assumed to be 0-255
srgb integers (incidentally, this is the format you will get from a PIL RGB image).
You can also pass in already linear data - to do this, set linear to True. This is
useful if you want to encode a version of your image resized to a smaller size (which
you should ideally do in linear colour).
"""
if components_x < 1 or components_x > 9 or components_y < 1 or components_y > 9:
raise ValueError("x and y component counts must be between 1 and 9 inclusive.")
height = float(len(image))
width = float(len(image[0]))
# Convert to linear if neeeded
image_linear = []
if linear == False:
for y in range(int(height)):
image_linear_line = []
for x in range(int(width)):
image_linear_line.append([
srgb_to_linear(image[y][x][0]),
srgb_to_linear(image[y][x][1]),
srgb_to_linear(image[y][x][2])
])
image_linear.append(image_linear_line)
else:
image_linear = image
# Calculate components
components = []
max_ac_component = 0.0
for j in range(components_y):
for i in range(components_x):
norm_factor = 1.0 if (i == 0 and j == 0) else 2.0
component = [0.0, 0.0, 0.0]
for y in range(int(height)):
for x in range(int(width)):
basis = norm_factor * math.cos(math.pi * float(i) * float(x) / width) * \
math.cos(math.pi * float(j) * float(y) / height)
component[0] += basis * image_linear[y][x][0]
component[1] += basis * image_linear[y][x][1]
component[2] += basis * image_linear[y][x][2]
component[0] /= (width * height)
component[1] /= (width * height)
component[2] /= (width * height)
components.append(component)
if not (i == 0 and j == 0):
max_ac_component = max(max_ac_component, abs(component[0]), abs(component[1]), abs(component[2]))
# Encode components
dc_value = (linear_to_srgb(components[0][0]) << 16) + \
(linear_to_srgb(components[0][1]) << 8) + \
linear_to_srgb(components[0][2])
quant_max_ac_component = int(max(0, min(82, math.floor(max_ac_component * 166 - 0.5))))
ac_component_norm_factor = float(quant_max_ac_component + 1) / 166.0
ac_values = []
for r, g, b in components[1:]:
ac_values.append(
int(max(0.0, min(18.0, math.floor(sign_pow(r / ac_component_norm_factor, 0.5) * 9.0 + 9.5)))) * 19 * 19 + \
int(max(0.0, min(18.0, math.floor(sign_pow(g / ac_component_norm_factor, 0.5) * 9.0 + 9.5)))) * 19 + \
int(max(0.0, min(18.0, math.floor(sign_pow(b / ac_component_norm_factor, 0.5) * 9.0 + 9.5))))
)
# Build final blurhash
blurhash = ""
blurhash += base83_encode((components_x - 1) + (components_y - 1) * 9, 1)
blurhash += base83_encode(quant_max_ac_component, 1)
blurhash += base83_encode(dc_value, 4)
for ac_value in ac_values:
blurhash += base83_encode(ac_value, 2)
return blurhash
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